Biometric notification system

ABSTRACT

The present invention provides a biometric notification system for selectively sending messages to interested recipients. In various embodiments, message trigger criteria, interested recipients, and message content may vary depending upon, among other things, the service being provided.

PRIORITY CLAIM AND INCORPORATION BY REFERENCE

This application is a continuation-in-part of U.S. patent applicationSer. No. 15/050,326 filed Feb. 22, 2016 which claims the benefit of U.S.Prov. Pat. App. No. 62/128,639 filed Mar. 5, 2015. This application is acontinuation-in-part of Ser. No. 14/612,207 filed Feb. 2, 2015, now U.S.Pat. No. 9,626,574, which is a continuation of U.S. patent applicationSer. No. 12/177,103 filed Jul. 21, 2008 now U.S. Pat. No. 9,141,863,both of which are incorporated herein in their entireties and for allpurposes.

(i) U.S. Pat. No. 5,561,718 issued Oct. 1, 1996, (ii) U.S. Pat. No.6,038,337 issued Mar. 14, 2000, (iii) U.S. Pat. No. 8,254,699 issuedAug. 28, 2012 and (iv) U.S. Pat. No. 8,798,375 issued Aug. 5, 2014 areincorporated herein in their entireties and for all purposes.

BACKGROUND OF THE INVENTION 1.0 Field of the Invention

The invention relates to a notification system. More particularly, theinvention relates to systems and methods that acquire and processbiometric information for discovering and acting on matched biometricfeature sets.

2.0 Discussion of the Related Art

Current facial recognition based biometric systems typically offerlittle more than a face comparison used primarily for the purpose ofidentifying an unknown person.

SUMMARY OF THE INVENTION

The present invention provides a biometric notification system forselectively sending messages to interested recipients. In variousembodiments, message trigger criteria, interested recipients, andmessage content may vary depending upon, inter alia, the service beingprovided.

An embodiment provides a biometric notification system (“BNS”) withfacial recognition and related services, the system comprising: pluraldigital video cameras (C₁, C₂ . . . C_(n)) that monitor respective zones(Z₁, Z₂ . . . Z_(n)) at a first site; a data processing system includinga processing facility and a database facility; a network interconnectingthe video cameras and the data processing facility; a video frameacquired from a video camera C_(x) in zone Z_(x) includes a firstcontent; a first facial feature set derived from the first content; adatabase of the database facility includes plural cases, each caseidentifies a person by linking a name with a second content, a secondfacial feature set, and a case group; a matched case discovered when theprocessing facility finds the first feature set matches a second featureset; and, a message sent to one or more interested recipients when theprocessing facility finds that message trigger criteria are met; whereinmessage trigger criteria include a requirement that a matched case isdiscovered.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention is described with reference to the accompanyingfigures. These figures, incorporated herein and forming part of thespecification, illustrate embodiments of the invention and, togetherwith the description, further serve to explain its principles enabling aperson skilled in the relevant art to make and use the invention.

FIG. 1 shows a biometric notification system implemented for a site.

FIG. 2 shows the biometric notification system of FIG. 1 in furtherdetail.

FIGS. 3A-C show the biometric notification system of FIG. 1 implementedfor single and multiple sites.

FIG. 4 shows functions of a processing facility of the biometricnotification system of FIG. 1

FIG. 5 shows functions of a database facility of the biometricnotification system of FIG. 1.

FIG. 6 shows a process of the biometric notification system of FIG. 1useful for identifying interested recipients.

FIGS. 7A-D show an embodiment of the biometric notification system ofFIG. 1 configured to provide location awareness and/or zone alertservices.

FIGS. 8A-B show an embodiment of the biometric notification system ofFIG. 1 configured to provide geofencing services.

FIG. 9A shows an embodiment of the biometric notification system of FIG.1 configured to provide intelligent video storage services.

FIG. 9B shows conceptually first in-first out memory of the biometricnotification system of FIG. 9A.

FIG. 10 shows an embodiment of the biometric notification system of FIG.1 configured to provide preference services.

FIGS. 11A-F show an embodiment of the biometric notification service ofFIG. 1 configured to provide archive services.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS

The disclosure provided herein describes examples of some embodiments ofthe invention. The designs, figures, and descriptions are non-limitingexamples of the embodiments they disclose. For example, otherembodiments of the disclosed device and/or method may or may not includeall of the features described herein. Moreover, disclosed advantages andbenefits may apply to only certain embodiments of the invention andshould not be used to limit the disclosed invention.

FIG. 1 shows an embodiment of the biometric notification system (“BNS”)of the present invention 100. As shown, a network 140 receives data 191from a site 120, and passes data 193 to a data processing system (“DPS”)160. The receiving devices of interested recipients 180 receive data 195from the network.

The site is an area of interest, for example a structure such asbuilding or a portion thereof. As shown, site 120 includes external andinternal boundaries such as external walls 122 and internal walls 124.Digital video cameras C1-C4 are arranged to cover respective zonesZ1-Z4.

The network provides a means for exchanging electronic information.Transport media include any of wire (e.g., copper), fiber (e.g., glass),or wireless such as a cellular network or an IEEE 802 network. Data 191,193, 195 exchanged with the network 140 may be transported by anysuitable means.

Data processing system functions include analyzing and acting onavailable data. As shown, digital video camera data such as video framesfrom cameras C1-C4 acquired at the site 120 are available to the dataprocessing system 160 via the network 140. See for example site data 191received by the network and network data 193 passed to the dataprocessing system. In various embodiments data available from thecameras and/or ancillary devices includes one or more of a siteidentifier, camera identifier, zone identifier, and a date/timeassociated with each video frame. The date/time “stamp” of a video framemay be referenced to a common time standard such as UTC (“tempsuniversel coordonne”) or GMT (Greenwich Mean Time).

Receiving devices of interested recipients 180 may include the devicesof site personnel and/or non-site personnel. Identification ofinterested recipients and/or their receiving devices may depend uponresults obtained when the data processing system 160 processes site data191. As shown, the receiving devices of interested recipients 180receive data 195 from the network 140.

In an embodiment, receiving devices of interested recipients 180 may beparticular devices assigned to particular persons, the same being knownto the DPS 160, such that a message sent to a particular device alwaysreaches a particular person. In another embodiment, receiving devices ofinterested recipients 180 may be associated with a particular user groupsuch that a message sent to a particular device always reaches aperson(s) in the user group. In yet other embodiments, messages are sentvia an addressing scheme and/or service such as a telephone number, textmessage, email address, short messaging service (“SMS”), public network,private network, or another suitable service utilizing an addressavailable to the DPS.

As skilled artisans will appreciate, any of the data exchanges with thenetwork may be bidirectional. For example, the bidirectional dataexchange 193 between the network 140 and the data processing system 160may provide for delivery of site data 191 to the data processing systemand for delivery of data processing system data or results 195 to thereceiving devices of interested recipients 180.

FIG. 2 shows an embodiment 200 of the biometric notification system ofFIG. 1. As shown, a network 140 receives data from a site 120. The sitedata includes data acquired from cameras C1-C4 via one or respective (asshown) transport media 231-234 extending between the cameras and thenetwork. In some embodiments the transport media are interconnected withthe network via a network switch such as an Ethernet switch.

The data processing system 160 receives site camera data from thenetwork 140 via a bidirectional data link 294 therebetween. Embodimentsof the data processing system 160 include an interconnection 262 forexchanging data with each of the network, a processing facility 264 anda database facility 266 via respective data links 294, 295, 296. In someembodiments, the interconnection 262 is provided at least in part by aserver backplane.

Processing facility 264 embodiments may include one or more processors265 and respective or shared complementary devices such as memory,input/output, and similar devices. In an embodiment, the processingfacility includes processor(s) or server(s) for one or more ofextracting facial feature sets, comparing facial feature sets,determining the receiving devices of interested recipients, andconstructing messages.

Database facility 266 is for storing at least one database 267. Databasefacility embodiments may utilize any type of memory suited to the tasksmentioned above or below, including one or more of semiconductor memorysuch as random access memory and solid state drives, optical memory suchas optical drives, and magnetic memory such as hard disk drives. Invarious embodiments, the database facility includes one or more of ahard drive array, a solid state drive array, a search engine, and adatabase server. Database facility embodiments include, among others,database facilities with database hardware collocated with a site,database hardware distributed among multiple different sites, anddatabase hardware that is centralized to support multiple sites.

Receiving devices 180 are for receiving messages from the network 140.In various embodiments, receiving devices are capable of receiving oneor more of text, graphics, pictures, motion pictures, symbols, andaudio. For example, receiving devices include any of wired and wirelessdevices such as telephones, cellular telephones, interconnectedcomputing devices, and non-cellular radio frequency devices.

Where messages are transported to recipients geographically distant fromthe site, off-site transmissions means include wide area networks,virtual private networks, Internet infrastructure, private wiredtransmission means, private wireless transmission means and the like. Inan embodiment, a network edge device such as a router 242 providesInternet connectivity for transport 270 of the message to the receivingdevice. And, in an embodiment, the message is transported via transportmedia local to the site 297.

The biometric notification system embodiments of FIGS. 1-2 may monitorsingle or multiple sites with respective or shared networks and dataprocessing systems. FIGS. 3A-C illustrate some of these embodiments300A-C.

FIG. 3A shows a biometric notification system supporting a single site300A. As shown, Site 1 is supported by a respective Network 1 and DPS 1(Data Processing System 1).

FIG. 3B shows a biometric notification system supporting two sites 300B.As shown, Sites 1 and 2 with respective Networks 1 and 2 share a singleDPS 1. A data Transport Link such as transport via the Internet providesa means for interconnecting the two networks.

FIG. 3C shows a biometric notification system supporting two sites 300C.As shown, Sites 1 and 2 have respective Networks 1 and 2 and respectiveDPS 1 and DPS 2. A data Transport Link such as transport via theInternet provides a means for interconnecting the two networks.

FIG. 4 shows functions of the processing facility 400. Processingfacility functions 402 provide for one or more of (i) obtain a facialfeature set 404, (ii) compare facial feature sets 406, (iii) determineinterested recipients 408, (iv) determine message content 410, and (v)other processing facility features 412.

Obtaining a facial feature set 404 provides a basis for matching and/oridentifying a person that appears in an image such as a video frame.This function may include one or both of isolating a face image as froma video frame and characterizing the face image via a facial featureset.

Face images may be isolated by techniques known to skilled artisans. Forexample, by pattern recognition wherein characteristic facial outlinesare used to discover the boundaries of a facial image within a frameincluding content unrelated to the facial image. Means for isolatingface images includes those disclosed in U.S. Pat. No. 8,121,349 filedAug. 31, 2009 which is now incorporated herein by reference in itsentirety and for all purposes.

Facial feature sets may be prepared by techniques known to skilledartisans. For example, metrics such as the relationship amongcharacteristic facial measurements, e.g., eye spacing versus earspacing, may be used to build a facial feature set with numeric valuesof multiple such relationships. Means for preparing facial feature setsinclude those disclosed in U.S. Pat. No. 5,835,616 filed Jun. 17, 1994and U.S. Pat. Pub. 2008/0193020 published Aug. 14, 2008, all of whichare now incorporated herein by reference in their entireties and for allpurposes.

Comparing facial feature sets 406 may be compared by quantifying theirdifferences, as by determining how individual or combined numeric facialfeature metrics differ and in particular on the magnitude of suchdifferences. In an embodiment, first and second facial feature setmetrics are quantified by respective equations as by curve fitting orsimilar techniques and the equations are manipulated by known techniquesto assess the likelihood that the persons represented by the facialfeature sets are the same person. Curve fitting techniques include leastsquares curve fits, polynomial curve fits, and interpolating polynomialcurve fits.

In various embodiments, a facial feature set is prepared for a personappearing in a video frame acquired by one of the video cameras C1-C4and in various embodiments the acquired facial feature set is comparedwith the facial feature set of a case in the case database 504. Othercomparisons include case to case comparison, imported facial feature setto case comparison, and imported facial set to imported facial featureset comparison.

Determination of interested recipients 408 identifies persons or devicesfor whom a message is intended. Interested recipients may be included ina pool of recipients known to the BNS, for example by inclusion in oneof the other databases 412. In an embodiment, a case in the casedatabase 504 is characterized by a case group (e.g., “shoplifters”) andinterested recipients are identified as a recipient group (e.g.,“security”) associated with the case group. Interested recipients mayalso be identified based on any of the site, time/date, function, jobfunction, location, present location and more as is further describedbelow.

In some embodiments, an interested recipients unknown to the BNS may bethe intended recipient of a message. For example, where an acquiredimage is matched with a case, the BNS may utilize non-BNS resources suchas the Internet to find the parole status of the person identified bythe case and an electronic address such as an email address of theperson's parole officer.

Determination of message content 410 assembles information thatcorresponds to the matched case. This content may include any of awritten message such as a textural or symbolic message, graphics,images, links or hyperlinks to related content, audio, and deviceinstructions or commands. Message content may be selected based on theinterested recipient, the matched person, case group, the site,time/date, function, job function, location, present location and moreas is further described below.

Other processing facility functions 412 may also be provided. Forexample, access to the BNS may be selectively granted to subscribers.Additional processing facility functions are further described below.

FIG. 5 shows functions of the database facility 500. Database facilityfunctions 502 provide for one or more of (i) a case database 504, (ii)subset(s) of a case database 506, (iii) other database(s) 508, (iv)subset(s) of other database(s) 510, (v) a search engine 512, and (vi)other database facility features 514.

Case database 504 contents include information about persons. In variousembodiments, the case database includes hundreds of cases. And, invarious embodiments, each case includes a facial feature set and mayinclude one or more of a corresponding name, image, and case group. Inan embodiment, for a plurality of cases, each case identifies a personby name, image, facial feature set, and one or more case groups. And, inan embodiment, all of the cases of the case database that are availablefor matching identify a person by name, image, facial feature set, andone or more case groups.

Subsets of case database 506 present a more limited universe of casesavailable for matching. For example, a subset may contain all of thecases identified by the “shoplifters” case group.

Other databases and subsets 508, 510 of these databases provide a meansof recording additional subject matter available to the BNS. For exampleany of people, instructions, and video footage may be recorded in such adatabase or database subset. As mentioned above, an other database maybe used to record pools of potential message recipients. In someembodiments, other databases are created and or populated “on the fly”as may occur when stream(s) of video frames are to be recorded.

Search engine 512 provides a data processing function. In particular,the search engine can respond to queries posed to the case 504 or otherdatabases 508. Rationale for inclusion of a search engine may includeone or more of multiple factors including speed, sharing of databases,modularity, and geography. For example, where all or some part of thedatabase facility 266 is remote from the processing facility 264 as inanother city or state, the database facility can respond to queriesusing the search engine. In some embodiments the search enginefunctionality is provided by a database server.

Other database facility functions 514 may also be provided. For example,access to the database may be selectively granted to subscribers.Additional database facility functions are further described below.

FIG. 6 illustrates a first process that may be used in notifyinginterested recipients 600. Execution of this process may result in thedelivery of one or more messages to one or more interested recipients.And in various embodiments, this process may be used to limit messagerecipients by particularly identifying one or more persons and/orreceiving devices to which the message will be sent.

A first facial feature set 602 and a second facial feature set 604 arepassed to a compare step 610. For example, (i) the first facial featureset is derived from a video frame acquired by a camera C1-C4 using theprocessing facility function to obtain the facial feature set 404 and(ii) the second facial feature set that of a case in the case database504. In various embodiments, second facial feature sets available forcomparison may be limited to the case database 504, a subset of the casedatabase 506, or they may be obtained from another database or resourceapart from the case database.

The first and second facial sets are compared 406 in a compare step 610to determine if there is a match. If there is no match, and anothersecond facial feature set is available for comparison with the firstfacial feature set 620, the process proceeds with this comparison 610.Where no additional second facial feature sets are available forcomparison, the process may end 622.

A match test step 612 may test for the presence of a match “+” or forthe absence of a match “−”. For example, where sending a message dependsupon finding a match, these symbols are not bracketed. And, wheresending a message depends on failure to find a match, these symbols arebracketed. Alternative match tests provide for, inter alia, sending amessage based on: (i) the discovery of a person identified by a secondfacial feature set available for comparison “+, −”; or (ii) discovery ofa person not identified by a second facial feature set available forcomparison “[+], [−]”.

When the match test is satisfied, a message may be sent 628 subject toany other criteria 614 and meeting any such other criteria 616. Forexample other criteria may include a case group test which may be met ornot. Failure to meet other criteria may cause a return to the “anothercomparison?” step. Executing the “send message” step 628 may cause areturn to the “another comparison?” step 618. In various embodimentswhere the match test is satisfied and other criteria, if any, are met,interested recipients may be determined 624 and message content may bedetermined 626 as steps prior to sending a message 628.

FIGS. 7A-D illustrate features of a BNS location awareness or zone alertservice 700A-D.

In FIG. 7A, plural zones Z1-Z6 of a site 712 are monitored by respectivecameras C1-C6 and a network 714 transports camera data to a dataprocessing system 716 that may be local to the site or remote from thesite. Persons 751, 753, 755 in respective zones Z1, Z5, Z4 are visibleto cameras C1, C5, C4.

In FIG. 7B, indicia of a case in a case database 267 are shown. Invarious embodiments, a person is identified by one or more of an image,facial feature set, case group, and location or zone alert.

In FIG. 7C, criteria for triggering a message are shown. In variousembodiments, trigger requirements include matching facial feature setsand other trigger requirements include a particular location and/or aparticular case group.

In an embodiment, message trigger criteria include (i) a requirementthat a person be matched with a case in the case database 267 and (ii)other message trigger criteria include a requirement that the matchedperson be discovered in a particular zone. Therefore, a message is notsent unless there is a match resulting from a video frame acquired in aparticular zone. For example, if other message trigger criteria of aparticular case CASEX identifying person 751 require only discovery inzone Z1, then a video frame acquired by camera C1 in zone Z1 that ismatched with CASEX match triggers a message concerning the person 751.Note that the camera providing a video frame from which a first facialfeature set is derived may be referred to as a match camera.

Message trigger criteria may include further requirements such asrequiring the case group of the matched case be a particular case groupand/or, requiring the match corresponds to a person known to siteoperators as a person of interest. For example, if other message triggercriteria of a particular case CASEX identifying person 751 requirediscovery in zone Z1 and a particular case group NOFLYLIST, then a videoframe acquired by camera C1 in zone Z1 that is matched with CASEXtriggers a message concerning person 751 only when indicia of CASEXinclude the NOFLYLIST case group.

Message recipients and or receiving devices of interested recipients maybe determined as mentioned above and by any of case group, job junction,territory, receiving device, location, and the like.

Just as the message trigger may depend on the match location, so too canrecipient(s) of the message be selected based on their location. Forexample, if persons 753 and 755 are site security personnel in a pool ofpotential message recipients, the BNS 700A may send the message to thereceiving device 754 of person 753 because zone Z5 is closer to zone Z1than is zone Z4.

In the above example, the BNS 700A may locate site personnel, forexample by limiting the second feature sets available for comparison tothose of site personnel.

FIG. 7D illustrates a site personnel locator. In the camera block 742video frames from all or a relevant subset of the site cameras, such ascameras in the discovery zone and adjacent zones, are acquired. Firstfacial feature sets extracted from the video frames 744 are comparedwith second facial feature sets 745 available from a site personneldatabase 743. In various embodiments, records of the site personneldatabase identify site personnel. Each such record includes a facialfeature set and other indicia such as one or more of name, number,image, job function, territory, and receiving device. Notably, thereference to “record” means not only individual database records, but insome embodiments related combinations of records for identifying aparticular person.

The feature sets 744, 745 are compared 746. Where there is a match 748,the person's location is documented 750, and a test for more cameras tobe checked is made 752. If more cameras are to be checked, the processreturns to the cameras block 742, acquires another video frame, andrepeats. Otherwise, the process ends 756.

Message content may include any of information from or derived from thecamera, case database, data processing system, and other sources such assources external to the BNS 700A. Message content may also be a functionof variables such as case group, interested recipient, and zone.

In an embodiment, site personnel receive a first message portion and asecond message portion. The first message portion includes an image ofthe matched person, the zone where video frame resulting in the matchwas acquired, and the time when the video frame was acquired. The secondmessage portion depends on the case group which indicates what caseinformation should be sent and what if any contemporaneous informationsuch as warrant status should be acquired and sent.

FIGS. 8A-B illustrate features of a BNS geofencing services 800A-B.

In the first geofencing service 800A of FIG. 8A, first and second facialfeature sets are compared 810. The first facial feature set 802 is froma video frame acquired by a camera 801 such as a camera Cx in zone Zx.The second facial feature set 804 is from a data storage resource suchas a database 805 that identifies persons to be excluded from zone Zx.In various embodiments, the second facial feature resource may be one ormore of the case database 267, a subset of the case database 269, a sitepersonnel database or its subset, another database or its subset, oranother suitable data storage resource known to skilled artisans.

If after the comparison 810 the match test 812 indicates the comparedfacial feature sets do not match, then to the extent another secondfacial feature set is available from the database 805, the processbegins again.

Because the database 805 provides facial feature sets of personsexcluded from zone Zx, a comparison 810 that results in a match 812meets at least the first criteria for sending a message. Other criteria814 such as date, time, presence in zone Zx of a non-excluded person mayalso be considered. For example, where the geofence triggers messagesonly on certain days (e.g. weekend) or only at certain times (e.g.weekdays after 5 PM). For example where the geofence does not triggermessages when a non-excluded or authorized person is present in zone Zx.

Where there is a match 812 and other criteria, if any, are met 816,intended recipients are determined 824. Intended recipients may bedetermined by any of the methods described above. Further, intendedrecipients may be predetermined by geofence parameters that nominateparticular persons, job functions, territories and/or their relatedreceiving devices 180 to receive messages resulting from operation ofthe geofence.

In a determine message content step 826, fixed message content and ormessage content that varies, for example with the matched person and/orintended recipient, is determined. The message content may be determinedby any of the methods described above. Further, the message content mayinclude one or more of the video frame that resulted in the match, thezone where and time when the frame was acquired, the name of the matchedperson, an image of the matched person, other identifyingcharacteristics of the matched person, and instructions for confrontingand/or dealing with the matched person.

In a send message step 828, the determined message(s) are sent to thereceiving device(s) 180 of interested recipient(s). In a return step818, the process returns to request another comparison in step 820. Ifthere are no additional comparisons, the process ends at step 822.

In the second geofencing service 800B of FIG. 8B, first and secondfacial feature sets 832, 834 are compared in a primary comparison 840.The first facial feature set is from a video frame acquired by camera831 such as camera Cy in zone Zy. The second facial feature set is froma data storage resource such as a database 835 that identifies personsnot excluded from zone Zy or persons whose access to zone Zy isauthorized. In various embodiments, the second facial feature resourcemay be one or more of the case database 267, a subset of the casedatabase 269, a site personnel database or its subset, another databaseor its subset, or another suitable data storage resource known toskilled artisans.

If after the primary comparison 840 a primary match test 842 indicatesthe compared facial feature sets match, then to the extent anothersecond facial feature set is available from the database 835, theprocess begins again.

Because the database 835 provides facial feature sets of persons notexcluded from zone Zy, a primary comparison 840 that results in no match842 meets at least the first criteria for sending a message. Othercriteria 844 such as date and time, or as mentioned above and below, mayalso be considered. For example, where the geofence triggers messagesonly on certain days (e.g. weekend) or only at certain times (e.g.weekdays after 5 PM).

Because the message trigger criteria include a no match condition, asecondary matching process may be used to identify the person that wasnot matched. For example, the matching process of FIG. 6 may beperformed as a secondary matching process (+/− without brackets at step612) where the first facial feature set is from the image that resultedin no match and the second facial feature sets are those of the casedatabase 267 or another database mentioned herein.

Where the primary match test 842 results in no match and other criteria844, if any, are met 846, intended recipients are determined 854.Intended recipients may be determined by any of the methods describedabove. Further, intended recipients may be predetermined by geofenceparameters that nominate particular persons, job functions, territoriesand/or their related receiving devices 180 to receive messages resultingfrom operation of the geofence.

In a determine message content step 856, fixed message content and ormessage content that varies, for example with the unmatched personand/or intended recipient, is determined. The message content may bedetermined by any of the methods described herein. Further, the messagecontent may include one or more of the video frame that resulted in nomatch, the zone where and time when the frame was acquired, unmatchedperson identifiers including image, and instructions for confrontingand/or dealing with the unmatched person.

In a send message step 858, the determined message(s) are sent to thereceiving device(s) 180 of interested recipient(s). In a return step848, the process returns to request another comparison in step 850. Ifthere are no additional comparisons, the process ends at step 852.

FIGS. 9A-B illustrate features of a BNS intelligent video storageservice 900A-B. Streams of video or video frames may be selected basedon matching and matching may be subject to whether or not a particularstream of video or video frame or facial feature set evident therein canbe associated with a selected attribute or a case group.

FIG. 9A shows a BNS wherein a network 904 interconnects a dataprocessing system (“DPS”) 906 with one of plural cameras 902. Inaddition to a processing facility 908 and a database facility 909, theDPS may include memory for tasks such as video storage.

In various embodiments, the BNS 900A captures streams of video from oneor more video cameras 902. Because copious amounts of memory aretypically required for storing video streams, embodiments of the BNSprovide for a memory buffer 914 and a memory 912 such as a video storagememory. The memory and memory buffer may be any of semiconductor memorysuch as random access memory, magnetic memory such as hard diskdrive(s), and optical memory such as optical drive(s).

In some embodiments, blocks of video frames held by the memory buffer914 are selectively moved to non-temporary storage 912 such as a diskdrive. For example, the memory buffer 914 may be a First In, First Out(“FIFO”) device such as a circular buffer that receives a stream ofvideo frames captured by the camera 902. At any point in time to, thecontents of the buffer may be saved to non-temporary storage such thatimages from an earlier time period (t_(−x) . . . t₀) are saved.

FIG. 9B illustrates video frames in a buffer 900B. Here, a firstin-first out memory buffer 914 provides space for eight video frames. Asshown, a frame [10] leaving the camera is an enqueue frame 921 and aframe [1] leaving the buffer is a dequeue frame 925. Between the enqueueand dequeue frames are frames [2 . . . 9] in time window (t⁻⁸ . . . t⁻⁰)held within the buffer memory 914. Notably, the buffer may be managed toenqueue and to dequeue entire blocks of data, for example where eachblock of data encompasses an entire video frame.

In an embodiment, a sequential stream of video frames from the videocamera 902 is received by a buffer 914 and the buffer contents, frames[2 . . . 9], are saved in a non-temporary video storage memory 912 whena second facial feature set (e.g., 604) is matched with a first facialfeature set (e.g., 602) derived from a target frame [5] in the buffer.As can now be appreciated, a decision to save the buffer saves pre-rollframes [2-4], target frame [5], and post-roll frames [6-9].

In various embodiments, a receiving device of an interested recipient(e.g., 180) that receives a message triggered by the match receives withthe message video derived from buffer contents or a hyperlink forviewing video derived from the buffer contents.

The size of a buffer memory 914 may be fixed or variable. For example,if a time period t_(a) is chosen, then the buffer may be sized toaccommodate x pre-roll frames and y post-roll frames. For example, wherex pre-roll frames occupy a time period t_(pre)=(t⁻⁸ . . . t⁻⁵) and ypost-roll frames occupy a time period t_(post)=(t⁻⁴ . . . t₀), thebuffer may be sized for t_(pre)>=t_(a) and t_(post)>=t_(a). The chosentime period t_(a) may be any of (i) a function of the time to match afirst facial feature (see e.g., 602) set with a second facial featureset (see e.g., 604), (ii) a function of the time to match a first facialfeature set with a fixed number of second facial feature sets, and (iii)a function of the time to match a first facial feature set with avariable number of second facial feature sets wherein t_(a) becomes avariable. Notably, the buffer may be symmetric about the target frame ornot (as shown).

In an embodiment, at the time a match is completed (see e.g., FIG. 6), aFIFO circular memory buffer holds x pre-roll frames and y post-rollframes, each of the x frames and y frames acquired during a respectiveacquisition time period t1, t2 in excess of a time period t3 required tocompare a first facial feature set of the target frame with all of thecases in a database (or database subset) such as the case database 267(or a case database subset 269).

And, in an embodiment plural circular memory buffers receive sequentialvideo streams from respective video cameras that monitor zones adjacentto zone Zx and these buffer contents are saved in video storage memorywhen the buffer contents are saved.

FIG. 10 illustrates features of a BNS preference service 1000. Ingeneral, preference services are directed to the care, preferences,and/or environment of a particular person or group of persons. Theexample of FIG. 10 illustrates features of a preference serviceoperating in guest accommodations such as a hotel.

As shown in the figure, a network 1040 interconnects devices such asreceiving devices of interested recipients (see e.g., 180) with a dataprocessing system 1042 similar to the DPS 200 of FIG. 2. The devices arelocated in a reception area 1012 and in a guest room 1022. In someembodiments a guest device such as a wireless device 1003 is used toaccess the network.

The DPS includes a guest database 1043 for identifying a particularguest via information such as name, image, facial feature set and otherparticulars such as organization, personal information, bookinginformation, automobile, preferences, history, and other information.Guest identifying information may be stored in one or plural relateddatabase record(s).

When a guest 1011 known to the DPS 1042, that is an expected guest,arrives in the hotel reception area 1012, a camera 1013 acquires a videoframe including the guest and the DPS matches the guest (see e.g., FIG.6) with a guest record in the guest database 1043. Other criteriarequired to trigger messages may be based on various checks andconfirmations such as comparing current and booking dates and comparingcurrent and booking time of arrival.

When the requirements for triggering messages are met, messages are sentto the receiving devices of interested recipients 180. In an embodiment,first and second messages are sent. The first message content includesidentification of the guest by name and image and is directed to thereceiving devices of greeting staff such as reception desk staff 1015and concierge staff 1017.

The second message content includes controller instruction(s) foradjusting and/or controlling operation of one or more appliances 1023 inthe guest room 1022 assigned to the matched guest. Appliances includecomfort devices such as heating ventilation and air conditioning,lighting devices such as electric lighting and window curtains, andentertainment devices such as audio systems and video systems.

In various embodiments, one or more user preferences may be entered in aguest database record by the guest or an agent of the guest. Forexample, a guest may at the time of booking or at another time use asuitable Internet 1030 access device 1003 such as a wireless device toaccess the hotel booking system to select guest preferences such as roomcomfort, lighting, and entertainment.

FIGS. 11A-F illustrate features of an archive service 1100A-F. Invarious embodiments, the archive service provides data storage for oneor more of video frames, information derived from video frames, relatedmetadata, and other information.

FIG. 11A shows a BNS serving one or multiple sites. A network 1104interconnects a data processing system 1102 and one 1106 or more 1108sites.

The DPS 1102 may be similar to the DPS 160 of FIG. 2 and furtherincludes an archive memory 1110 such as online or offline storagefacility using any one or more of the memory technologies describedabove, for example disk drives. DPS locations may be proximate or withina site and remote with respect to one or multiple sites using longdistance or wide area network data transport such as the wired orwireless data transport means described above.

The network 1104 may be similar to the network 140 of FIG. 2. In anembodiment, the network interconnects the DPS 1102 with a first site S1.And, in an embodiment the network interconnects the DPS with a firstsite S1 and a second site S2 (as shown).

The sites are divided into zones such that site 1 includes zones Z1, Z2monitored by respective cameras C1, C2 and site 2 includes zones Z1, Z2monitored by respective video cameras C1, C2. In the figures,designations such as S1C1, S2C1 distinguish the cameras of site 1 fromthose of site 2.

In various embodiments, the archive memory 1110 provides storage in adatabase(s), database subsets, files, and other suitable means of memoryutilization known to skilled artisans. In the embodiment shown, a folderanalogy is used. In particular, storage usage is depicted with foldersfor each of four cameras, S1C1, S1C2, S2C1, S2C2.

Folder content includes information derived from cameras and in variousembodiments video frame streams such as continuous video and sequentialsets of video frames such as frames acquired at particular timeintervals, for example 1 frame/second.

FIG. 11B shows an embodiment of an archive folder. Here, the folder S1A1contains a sequence of blocks such as blocks including video frames. Invarious embodiments, video frames are acquired from site 1 (S1) camera 1(C1) in zone 1 (Z1) such as a sequence acquired over a substantial timeperiod, for example during site working hours over a period of weeks,months, or years.

For each video frame with a facial image, a second facial feature set isassociated with the video frame. For example, second facial feature setsmay be obtained 404 in an online or off-line process that iscontemporaneous with video frame acquisition or not. And, for each videoframe with a facial image, a commonly referenced date and time may beassociated with the video frame.

Notably, folder SxCx may receive only frames with a facial image, anyother frames being discarded or redirected beforehand. In an alternativemode, frames without a facial image may be purged from the folder.

In an embodiment, an archive service builds an archive in plural foldersSxCx of an archive memory 1110. Each archive folder may receivesequential video frames from a respective video camera Cx in zone Zx atsite Sx. For each video frame including a facial image, a second facialfeature set is derived from the facial image of the video frame and acommonly referenced date time and stamp is associated with the videoframe. This information provides a means for tracking a particularindividual or person of interest. For example, comparing the firstfacial feature set of the person of interest with the second facialfeature sets of the video archive identifies video frames where theperson of interest is present. Matched video frames may be loadedchronologically into a playback folder for tracking the person ofinterest.

FIG. 11C shows storage folders and a playback folder of an archiveservice 1100C. The storage folders S1C1, S1C2 provide data and metadatastorage for information associated with cameras C1, C2 at site 1.Folders S1C1, S2C2 store blocks of information 1102, 1104, for examplesequential blocks corresponding to a chronological sequence of videoframes beginning Oct. 1, 2014, 11:50 PM UTC.

The storage folders S1C1, S1C2 may store blocks of data (blocks 1-10shown). Each block includes or refers to data or indicia of one or moreof a video frame, a facial image obtained from the video frame, a secondfacial feature set derived from the facial image, a commonly referencedtime and date stamp, a site identifier, a camera identifier, and a zoneidentifier. Crosshatched block sequences S1C1 (5-10) and S1C2 (2-4)indicate matched block sequences wherein a second facial feature in eachof these blocks matches a first facial feature set of a person ofinterest.

In an embodiment, a playback folder (not shown) is loaded with videoframes corresponding to S1C1 (5-10) for playback in chronological order.This embodiment provides, for example, tracking in a single zone Z1 atsite 1.

In another embodiment, the playback folder is loaded with a splicedsequence of video frames. Here, video frames S1C2 (2-4) spliced with thevideo frames of S1C1 (5-10) are loaded into the playback folder forplayback in chronological order. This embodiment provides, for example,tracking in multiple zones Z1, Z2 at site 1.

FIG. 11D shows an archive service with a first automated video splicingfeature 1100D. Here, the contents 1112 and 1114 of the folders S1C1,S1C2 overlap chronologically such that three blocks (5-7) of S1C1overlap with three blocks (5-7) of S1C2. The overlap might be eliminatedby splicing the matched blocks (2-7) of S1C2 with the matched blocks(5-10) of S1C1. However, to the extent a chronological sequence ofblocks is desired, some blocks must be eliminated. In a firstembodiment, sufficient blocks are removed to eliminate the overlap.

In a second embodiment blocks are removed such that S1C2 blocks arespliced with S1C1 blocks at an approximate overlap midpoint, here block6. In particular, blocks S1C2 (6-7) are removed and block S1C1 (5) isremoved such that a splice occurs between blocks S1C2 (5) and S1C1 (6).This results in a chronological sequence of matched blocks, S1C2 (2)through S1C1 (1), being loaded into the playback folder 1116. Theseembodiments provide, for example, tracking in multiple zones Z1, Z2 atsite 1 with elimination of overlaps to provide a strictly chronologicalplayback sequence.

FIG. 11E shows an archive service with a second automated video splicingfeature 1100E. Here, the contents 1122 and 1124 of the folders S1C1,S1C2 overlap chronologically such that three matched blocks (4-6) ofS1C1 overlap with three matched blocks (4-6) of S1C2.

As seen, the initial blocks S1C1 (4), S1C2 (4) overlap temporally. In anembodiment, the longer of the two block sequences S1C1 (4-10) is loadedinto the playback folder. This embodiment provides, for example,tracking in single zone Z1 at site 1.

In other embodiments, the two block sequences S1C1 (4-10) and S1C2 (4-6)are spliced with some blocks removed to provide, for example, a strictlychronological playback sequence. One such embodiment gives preference tothe blocks of the camera closest to the person of interest, determinedfor example via comparison of facial areas in the initial blocks of eachblock sequence, the larger of the compared areas determining thepreference.

The figure illustrates one such assemblage of playback frames 1126 wherethe initial block (4) of the matched blocks S1C2 (4-6) is determined tohave a larger facial image than the initial block (4) of the matchedblocks S1C2 (4-10). As seen, blocks S1C1 (4-6) are removed and sequencesS1C2 (4-6) and S1C1 (7-10) are joined at a splice. In other embodiments,once the preferred block sequence is determined, the splice may belocated by any suitable method including suitable methods describedabove. These embodiments provide, for example, tracking in multiplezones Z1, Z2 at site 1 with selection of a preferred block sequence andelimination of overlaps to provide a strictly chronological playbacksequence.

As shown in FIG. 11A above, the archive service is not limited to asingle site. Rather, the embodiments of FIGS. 11C-E might just as easilybe used to assemble a playback folder where cameras including camera C1are located at a first site and cameras including camera C2 are locatedat a second sight. Moreover, irrespective of the site locations such asinter campus, intercity, interstate or intercountry, embodimentsutilizing a common time base such as a commonly referenced UTC timestamps enables assemblage of a chronological sequence of video frames ina playback folder.

FIG. 11F shows a multisite archive service with an automated videosplicing feature 1100F. Here, each of two sites S1, S2 have multiplecameras, for example site 1 cameras C1, C2 and site 2 cameras C1, C2.Archive folders corresponding to the cameras are S1C1, S1C2, S2C1, S2C2(see e.g., FIG. 11A).

Folder S1C1 contains blocks (1-10) 1132 corresponding to camera C1 andwith matched blocks (5-8). Folder S1C2 contains blocks (1-10) 1134corresponding to camera C2 and with matched blocks (4-6). Folder S2C1contains blocks (1-10) 1142 corresponding to camera C3 and with matchedblocks (4-5). Folder S2C2 contains blocks (1-10) 1144 corresponding tocamera C4 and with matched blocks (1-4). The matched blockscorresponding with site 1 cameras overlap at blocks (5, 6) and thematched blocks corresponding with site 2 cameras overlap at block (4).

As seen in the playback folder contents 1146, matched frames from eachof cameras C1-C4 are assembled in a chronological sequence such that aperson of interest can be observed moving from zone Z2 to zone Z1 atsite 1 and later moving from zone Z2 to zone Z1 at site 2. Notably, fromthe 13 matched blocks, a corresponding set of 13 video frames wasreduced to a set of 10 sequential video frames. These frames appear inthe contents 1136 of the video playback folder.

In the video playback folder 1146, splices are shown between video framepairs S1C2 (5):S1C16 and S2C2 (3):S1C1 (4). These splices result fromeliminating the overlap of video frames corresponding with (i) site 1cameras C1, C2 and (ii) site 2 cameras C1, C2. Frames may be removed byany suitable method including suitable methods mentioned above. Where,as here, video frames from multiple sites are available, site splicessuch as third splice S1C1 (8):S2C2 (1) may be used to join the sequencesof video frames.

While various embodiments of the present invention have been describedabove, it should be understood that they have been presented by way ofexample only, and not limitation. It will be apparent to those skilledin the art that various changes in the form and details can be madewithout departing from the spirit and scope of the invention. As such,the breadth and scope of the present invention should not be limited bythe above-described exemplary embodiments, but should be defined only inaccordance with the following claims and equivalents thereof.

What is claimed is:
 1. A biometric notification system (“BNS”) withfacial recognition and related services, the system comprising: pluraldigital video cameras (C₁ . . . C_(n)) that monitor respective zones (Z₁. . . Z_(n)) at a first site; a processing system including a processingfacility and a database facility; a network interconnecting the videocameras and the data processing facility; a video frame acquired from avideo camera C_(x) in zone Z_(x) includes a first content and a firstfacial feature set derived from the first content; a database of thedatabase facility includes plural cases, each case identifies a personby linking a name with a second facial feature set and a case group; amatched case discovered when the processing facility finds the firstfeature set matches a second feature set; message trigger criteriainclude a requirement that a matched case is discovered; a userpreference service wherein the site is a building and a camera C_(x) islocated in a building reception area Z_(x); first and second messagesare sent when a matched case includes a case group that identifies theperson as an expected guest; the first message content includesidentification of the guest by name and image and a recipient of thefirst message is a security staff member; and, the second messagecontent includes a controller instruction for adjusting operation of anappliance that attends to the guest.
 2. A BNS with facial recognitionand related services, the system comprising: plural digital videocameras (C₁ . . . C_(n)) that monitor respective zones (Z₁ . . . Z_(n))at a first site; a processing system including a processing facility anda database facility; a network interconnecting the video cameras and thedata processing facility; a video frame acquired from a video cameraC_(x) in zone Z_(x) includes a first content and a first facial featureset derived from the first content; a database of the database facilityincludes plural cases, each case identifies a person by linking a namewith a second facial feature set and a case group; a matched casediscovered when the processing facility finds the first feature setmatches a second feature set; message trigger criteria include arequirement that a matched case is discovered; and, a first geofencingservice for recognizing a person excluded from a zone; wherein only asubset of the cases in the database is available for comparison with thefirst feature set, the subset of cases consisting of persons excludedfrom zone Z_(x) and discovery of a matched case results in a messagebeing sent to site security, the message advising the occurrence of asecurity breach and the name, image, and zone of the person of thematched case.
 3. A BNS with facial recognition and related services, thesystem comprising: plural digital video cameras (C₁ . . . C_(n)) thatmonitor respective zones (Z₁ . . . Z_(n)) at a first site; a processingsystem including a processing facility and a database facility; anetwork interconnecting the video cameras and the data processingfacility; a video frame acquired from a video camera C_(x) in zone Z_(x)includes a first content and a first facial feature set derived from thefirst content; a database of the database facility includes pluralcases, each case identifies a person by linking a name with a secondfacial feature set and a case group; a matched case discovered when theprocessing facility finds the first feature set matches a second featureset; message trigger criteria include a requirement that a matched caseis discovered; and, a second geofencing service for recognizing a personnot excluded from a zone; wherein only a subset of cases in the databaseis available for comparison with a first feature set, the subset ofcases consisting of persons not excluded from zone Z_(x) and failure todiscover a matched case results in a message being sent to sitesecurity, the message advising the occurrence of a security breach andthe image and zone of the person that could not be matched.
 4. A BNSwith facial recognition and related services, the system comprising:plural digital video cameras (C₁ . . . C_(n)) that monitor respectivezones (Z₁ . . . Z_(n)) at a first site; a processing system including aprocessing facility and a database facility; a network interconnectingthe video cameras and the data processing facility; a video frameacquired from a video camera C_(x) in zone Z_(x) includes a firstcontent and a first facial feature set derived from the first content; adatabase of the database facility includes plural cases, each caseidentifies a person by linking a name with a second facial feature setand a case group; a matched case discovered when the processing facilityfinds the first feature set matches a second feature set; messagetrigger criteria include a requirement that a matched case isdiscovered; and, a first intelligent video storage service; wherein asequential stream of video frames from a match camera C_(x) is receivedby a circular memory buffer and the buffer contents B_(x) are saved invideo storage memory when a second facial feature set is matched with afirst facial feature set derived from a target frame in the circularmemory buffer and wherein an interested recipient that receives amessage triggered by the match receives with the message a hyperlink forviewing the buffer contents saved in video memory storage.
 5. The BNS ofclaim 4, wherein at the time the match is completed, the circular memorybuffer holds x frames acquired before the target frame (“pre-rollframes”) and y frames acquired after the target frame (“post-rollframes”), each of the x frames and the y frames acquired during arespective acquisition time period t1, t2 in excess of a time period t3required to compare the first facial feature set of the target framewith all of the cases in the database.
 6. The BNS of claim 4 wherein thecircular buffer size varies with the number of second facial featuresets available for comparison with the first facial feature set of thetarget frame.
 7. The BNS of claim 4 wherein plural circular memorybuffers receive sequential video streams from respective cameras thatmonitor zones adjacent to Z_(x) and these buffer contents are saved invideo storage memory when the buffer contents B_(x) are saved.
 8. A BNSwith facial recognition and related services, the system comprising:plural digital video cameras (C₁ . . . C_(n)) that monitor respectivezones (Z₁ . . . Z_(n)) at a first site; a processing system including aprocessing facility and a database facility; a network interconnectingthe video cameras and the data processing facility; a video frameacquired from a video camera C_(x) in zone Z_(x) includes a firstcontent and a first facial feature set derived from the first content; adatabase of the database facility includes plural cases, each caseidentifies a person by linking a name with a second facial feature setand a case group; a matched case discovered when the processing facilityfinds the first feature set matches a second feature set; messagetrigger criteria include a requirement that a matched case isdiscovered; an archive memory with plural archive folders; and, aservice for building an archive in the archive memory; wherein (i) eacharchive folder receives sequential video frames from a respective videocamera C_(x) in zone Z_(x) and (ii) for each video frame including afacial image, a second facial feature set derived from the facial imageis associated with the video frame and a commonly referenced date timeand stamp is associated with the video frame.
 9. The BNS of claim 8further comprising: a facial feature set of a particular person ofinterest; wherein the facial feature set of the particular person ofinterest is compared with the facial feature sets of archive folders andmatched folders are identified; wherein the video frames of the matchedfolders are arranged for playback in chronological order.
 10. The BNS ofclaim 9 further comprising: a first automated video editing feature;wherein if a sequence of frames from a first camera to see theparticular person of interest overlaps chronologically with a sequenceof frames from a second camera to see the particular person of interest,then sufficient frames are removed from the overlap to eliminate theoverlap.
 11. The BNS of claim 10 wherein the first and second cameraframes that are removed result in a splice of the first camera frames tothe second camera frames at an approximate overlap midpoint.
 12. The BNSof claim 10 further comprising: proximity sensing for determining adistance between the camera and the person of interest; and, a secondautomated video editing feature; wherein if the initial frame of thefirst camera frame sequence and the initial frame of the second cameraframe sequence are temporally coincident, then the frame sequences arespliced to provide playback of frames of the camera closest to theparticular person of interest before playback of frames of the othercamera.
 13. A BNS with facial recognition and related services, themethod comprising: providing plural digital video cameras (C₁ . . .C_(n)) that monitor respective zones (Z₁ . . . Z_(n)) at a first site, aprocessing system including a processing facility and a databasefacility, a network interconnecting the video cameras and the dataprocessing facility, a video frame acquired from a video camera C_(x) inzone Z_(x) including a first content and a first facial feature setderived from the first content, a database of the database facilityincluding plural cases, each case identifying a person by linking a namewith a second facial feature set and a case group, a matched casediscovered when the processing facility finds the first feature setmatches a second feature set, message trigger criteria including arequirement that a matched case is discovered, and a user preferenceservice wherein the site is a building and a camera C_(x) is located ina building reception area Z_(x); and, sending first and second messageswhen a matched case includes a case group that identifies the person asan expected guest; wherein the first message content includesidentification of the guest by name and image, a recipient of the firstmessage is a security staff member, and the second message contentincludes a controller instruction for adjusting operation of anappliance that attends to the guest.
 14. A BNS with facial recognitionand related services, the method comprising: providing plural digitalvideo cameras (C₁ . . . C_(n)) that monitor respective zones (Z₁ . . .Z_(n)) at a first site, a processing system including a processingfacility and a database facility, a network interconnecting the videocameras and the data processing facility, a video frame acquired from avideo camera C_(x) in zone Z_(x) including a first content and a firstfacial feature set derived from the first content, a database of thedatabase facility including plural cases, each case identifying a personby linking a name with a second facial feature set and a case group, amatched case discovered when the processing facility finds the firstfeature set matches a second feature set, and message trigger criteriaincluding a requirement that a matched case is discovered; providing afirst geofencing service for recognizing a person excluded from a zone;wherein only a subset of the cases in the database is available forcomparison with the first feature set, the subset of cases consisting ofpersons excluded from zone Z_(x) and discovery of a matched case resultsin a message being sent to site security, the message advising theoccurrence of a security breach and the name, image, and zone of theperson of the matched case.
 15. A BNS with facial recognition andrelated services, the method comprising: providing plural digital videocameras (C₁ . . . C_(n)) that monitor respective zones (Z₁ . . . Z_(n))at a first site, a processing system including a processing facility anda database facility, a network interconnecting the video cameras and thedata processing facility, a video frame acquired from a video cameraC_(x) in zone Z_(x) including a first content and a first facial featureset derived from the first content, a database of the database facilityincluding plural cases, each case identifying a person by linking a namewith a second facial feature set and a case group, a matched casediscovered when the processing facility finds the first feature setmatches a second feature set, and message trigger criteria including arequirement that a matched case is discovered; providing a secondgeofencing service for recognizing a person not excluded from a zone;wherein only a subset of cases in the database is available forcomparison with a first feature set, the subset of cases consists ofpersons not excluded from zone Z_(x), failure to discover a matched caseresults in a message being sent to site security, the message advisesthe occurrence of a security breach and the image and zone of the personthat could not be matched.
 16. A BNS with facial recognition and relatedservices, the method comprising: providing plural digital video cameras(C₁ . . . C_(n)) that monitor respective zones (Z₁ . . . Z_(n)) at afirst site, a processing system including a processing facility and adatabase facility, a network interconnecting the video cameras and thedata processing facility, a video frame acquired from a video cameraC_(x) in zone Z_(x) including a first content and a first facial featureset derived from the first content, a database of the database facilityincluding plural cases, each case identifying a person by linking a namewith a second facial feature set and a case group, a matched casediscovered when the processing facility finds the first feature setmatches a second feature set, and message trigger criteria including arequirement that a matched case is discovered; providing a firstintelligent video storage service; wherein a sequential stream of videoframes from a match camera C_(x) is received by a circular memory bufferand the buffer contents B are saved in video storage memory when asecond facial feature set is matched with a first facial feature setderived from a target frame in the circular memory buffer and aninterested recipient that receives a message triggered by the matchreceives with the message a hyperlink for viewing the buffer contentssaved in video memory storage.
 17. A BNS with facial recognition andrelated services, the method comprising: providing plural digital videocameras (C₁ . . . C_(n)) that monitor respective zones (Z₁ . . . Z_(n))at a first site, a processing system including a processing facility anda database facility, a network interconnecting the video cameras and thedata processing facility, a video frame acquired from a video cameraC_(x) in zone Z_(x) including a first content and a first facial featureset derived from the first content, a database of the database facilityincluding plural cases, each case identifying a person by linking a namewith a second facial feature set and a case group, a matched casediscovered when the processing facility finds the first feature setmatches a second feature set, and message trigger criteria including arequirement that a matched case is discovered; wherein at the time thematch is completed, the circular memory buffer holds x frames acquiredbefore the target frame (“pre-roll frames”) and y frames acquired afterthe target frame (“post-roll frames”), each of the x frames and the yframes acquired during a respective acquisition time period t1, t2 inexcess of a time period t3 required to compare the first facial featureset of the target frame with all of the cases in the database.
 18. A BNSwith facial recognition and related services, the method comprising:providing plural digital video cameras (C₁ . . . C_(n)) that monitorrespective zones (Z₁ . . . Z_(n)) at a first site, a processing systemincluding a processing facility and a database facility, a networkinterconnecting the video cameras and the data processing facility, avideo frame acquired from a video camera C_(x) in zone Z_(x) including afirst content and a first facial feature set derived from the firstcontent, a database of the database facility including plural cases,each case identifying a person by linking a name with a second facialfeature set and a case group, a matched case discovered when theprocessing facility finds the first feature set matches a second featureset, and message trigger criteria including a requirement that a matchedcase is discovered; wherein the circular buffer size varies with thenumber of second facial feature sets available for comparison with thefirst facial feature set of the target frame.
 19. A BNS with facialrecognition and related services, the method comprising: providingplural digital video cameras (C₁ . . . C_(n)) that monitor respectivezones (Z₁ . . . Z_(n)) at a first site, a processing system including aprocessing facility and a database facility, a network interconnectingthe video cameras and the data processing facility, a video frameacquired from a video camera C_(x) in zone Z_(x) including a firstcontent and a first facial feature set derived from the first content, adatabase of the database facility including plural cases, each caseidentifying a person by linking a name with a second facial feature setand a case group, a matched case discovered when the processing facilityfinds the first feature set matches a second feature set, and messagetrigger criteria including a requirement that a matched case isdiscovered; wherein plural circular memory buffers receive sequentialvideo streams from respective cameras that monitor zones adjacent toZ_(x) and these buffer contents are saved in video storage memory whenthe buffer contents B_(x) are saved.
 20. A BNS with facial recognitionand related services, the method comprising: providing plural digitalvideo cameras (C₁ . . . C_(n)) that monitor respective zones (Z₁ . . .Z_(n)) at a first site, a processing system including a processingfacility and a database facility, a network interconnecting the videocameras and the data processing facility, a video frame acquired from avideo camera C_(x) in zone Z_(x) including a first content and a firstfacial feature set derived from the first content, a database of thedatabase facility including plural cases, each case identifying a personby linking a name with a second facial feature set and a case group, amatched case discovered when the processing facility finds the firstfeature set matches a second feature set, and message trigger criteriaincluding a requirement that a matched case is discovered; and,providing an archive memory with plural archive folders and a servicefor building an archive in the archive memory; wherein (i) each archivefolder receives sequential video frames from a respective video cameraC_(x) in zone Z_(x) and (ii) for each video frame including a facialimage, a second facial feature set derived from the facial image isassociated with the video frame and a commonly referenced date time andstamp is associated with the video frame.
 21. A BNS with facialrecognition and related services, the method comprising: providingplural digital video cameras (C₁ . . . C_(n)) that monitor respectivezones (Z₁ . . . Z_(n)) at a first site, a processing system including aprocessing facility and a database facility, a network interconnectingthe video cameras and the data processing facility, a video frameacquired from a video camera C_(x) in zone Z_(x) including a firstcontent and a first facial feature set derived from the first content, adatabase of the database facility including plural cases, each caseidentifying a person by linking a name with a second facial feature setand a case group, a matched case discovered when the processing facilityfinds the first feature set matches a second feature set, and messagetrigger criteria including a requirement that a matched case isdiscovered; providing proximity sensing for determining a distancebetween the camera and the person of interest; and, providing a secondautomated video editing feature; wherein if the initial frame of thefirst camera frame sequence and the initial frame of the second cameraframe sequence are temporally coincident, then the frame sequences arespliced to provide playback of frames of the camera closest to theperson of interest before playback of frames of the other camera.